Map-Aided Integrity Monitoring of a Land Vehicle Navigation System
Map-Aided Integrity Monitoring of a Land Vehicle Navigation System
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DOI：
10.1109/tits.2012.2187196
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发表时间：
2012-06-01
影响因子：
8.5
通讯作者：
Zheng, Yuheng
中科院分区：
文献类型：
--
作者：
Velaga, Nagendra R.;Quddus, Mohammed A.;Zheng, Yuheng
用户一级完整性监测的概念已成功地应用于航空运输导航系统，其主要重点是与全球定位系统数据处理链有关的误差。很少有研究工作一直致力于研究的情况下，陆地车辆导航系统的完整性监测。主要的区别是，它也是必要的，以考虑与空间地图和地图匹配（MM）的过程中，监测陆地车辆导航系统的完整性的错误。这是因为这两个组件在陆地车辆导航中起着至关重要的作用。迄今为止，研究的重点是从GPS获得的原始定位数据的完整性或MM过程和数字地图误差的完整性。在本文中，这些来源的错误被同时考虑。因此，本文的主要贡献是报告的用户级完整性监控系统，同时考虑到所有潜在的误差源与导航系统，并考虑操作环境，以进一步提高性能的发展。与空间路线图相关的错误受到特别关注。两个知识为基础的模糊推理系统的开发来衡量的完整性规模。使用在诺丁汉和伦敦收集的现场数据评估完整性方法的性能。K.结果表明，完整性的方法提供了有效的警告98.2%和99.4%的时间定位数据在混合操作环境中，在诺丁汉和郊区的伦敦，分别。
The concept of user-level integrity monitoring has been successfully applied to air transport navigation systems, where the main focus is on the errors associated with the Global Positioning System (GPS)-data-processing chain. Little research effort has been devoted to the study of integrity monitoring for the case of land vehicle navigation systems. The primary difference is that it is also necessary to consider errors associated with a spatial map and a map-matching (MM) process when monitoring the integrity of a land vehicle navigation system. This is because these two components play a vital role in land vehicle navigation. To date, research has focused on either the integrity of raw positioning data obtained from GPS or the integrity of the MM process and digital map errors. In this paper, these sources of error are simultaneously considered. Therefore, the main contribution of this paper is to report the development of a user-level integrity-monitoring system that concurrently takes into account all the potential error sources associated with a navigation system and considers the operational environment to further improve performance. Errors associated with a spatial road map are given special attention. Two knowledge-based fuzzy inference systems were developed to measure the integrity scale. The performance of the integrity method was assessed using field data collected in Nottingham and London, U. K. The results indicate that the integrity method provides valid warnings 98.2% and 99.4% of the time for positioning data in a mixed operational environment in Nottingham and suburban areas of London, respectively.